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ARS Home » Pacific West Area » Corvallis, Oregon » Forage Seed and Cereal Research Unit » Research » Publications at this Location » Publication #400183

Research Project: Improving Plant, Soil, and Cropping Systems Health and Productivity through Advanced Integration of Comprehensive Management Practices

Location: Forage Seed and Cereal Research Unit

Title: Flight phenology and landscape predictors of invasive Coleophora deauratella populations in Oregon and New Zealand red clover

item Dorman, Seth
item KAUR, NAVNEET - Oregon State University
item ANDERSON, NICOLE - Oregon State University
item SIM, RICHARD - Pyne Gould Guinness Limited And Agricom Limited (PGG) Wrightson Seeds
item TANNER, CHRISTY - Oregon State University
item WALENTA, DARRIN - Oregon State University
item Cooper, William - Rodney

Submitted to: Journal of Pest Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/2/2023
Publication Date: 9/7/2023
Citation: Dorman, S.J., Kaur, N., Anderson, N., Sim, R., Tanner, C., Walenta, D., Cooper, W.R. 2023. Flight phenology and landscape predictors of invasive Coleophora deauratella populations in Oregon and New Zealand red clover. Journal of Pest Science.

Interpretive Summary: The red clover casebearer moth (Coleophora deauratella) is an invasive pest in red clover seed production, recently introduced in Oregon and New Zealand. We sampled commercial red clover fields throughout the growing season in two production regions in Oregon (Willamette Valley and eastern Oregon) and New Zealand to observe adult red clover casebearer activity using female sex pheromone lures. Field observations of adult males were used to develop models that predict the phenology or timing of adult activity using growing degree day accumulations (heat units above biologically relevant temperature thresholds). We demonstrated that phenology models could accurately predict seasonal flight with new data to inform mitigation strategies and develop decision support tools. We also investigated the effects of landscapes surrounding sampled red clover farms on red clover casebearer populations using molecular analyses of gut contents in early-season moth collections and spatial Bayesian models that account for spatial random effects. We found that land area intensification of clover production and grassland (amount of land area over time) were positively associated with red clover casebearer populations. These results can be used to forecast red clover casebearer risk across space and time and advise integrated pest management practices.

Technical Abstract: Red clover casebearer moth (Coleophora deauratella) (Leinig and Zeller) (Lepidoptera: Coleophoridae) is an invasive insect pest in red clover (Trifolium pratense L.) seed production systems in North America and New Zealand. Recent discoveries of C. deauratella in Oregon and New Zealand prompted research investigating the seasonal phenology and population dynamics of C. deauratella to inform management strategies and develop a risk prediction framework to mitigate outbreak severity. We sampled 76 site-years across three geographic regions, including western (Willamette Valley) and eastern Oregon and New Zealand. An attractant-based trap network was deployed across sampled regions using a female sex pheromone to lure male moths in commercial red clover seed production fields. Remotely sensed temperature and landscape composition data were extracted for phenological and geospatial modeling. Nonlinear logistic regression was used to develop regionally explicit phenology models that predict the unimodal timing of C. deauratella flights. Molecular gut content analyses revealed the dietary history of early season captures and informed landscape analysis covariate selection. A spatial Bayesian generalized linear mixed model (GLMM) was developed to test landscape-level effects of landscape composition and configuration predictors on C. deauratella abundance. The spatiotemporal dominance of clover and grassland land area was positively associated with C. deauratella populations. These results can be used to forecast C. deauratella risk across space and time and advise integrated pest management practices.